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id | node_id | number | title | user | state | locked | assignee | milestone | comments | created_at | updated_at ▲ | closed_at | author_association | active_lock_reason | draft | pull_request | body | reactions | performed_via_github_app | state_reason | repo | type |
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1555829604 | PR_kwDOAMm_X85IeHqq | 7475 | Update error message when saving multiindex | OriolAbril 23738400 | closed | 0 | 0 | 2023-01-24T23:44:14Z | 2023-02-25T11:57:59Z | 2023-02-24T20:16:43Z | CONTRIBUTOR | 0 | pydata/xarray/pulls/7475 | I have updated the error message that gets printed when trying to save a multiindex following some discussion in an ArviZ repo with @dcherian.
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1240234432 | I_kwDOAMm_X85J7HnA | 6620 | Using the html repr in the documentation | OriolAbril 23738400 | open | 0 | 1 | 2022-05-18T16:53:46Z | 2022-05-18T17:46:26Z | CONTRIBUTOR | What is your issue?most (if not all) of xarray documentation is written as rst files and using the ipython directive. Due to this, the html repr is not use in the documentation. I find the html repr to be much more informative and intuitive, especially for beginners and I think it would be great to use it in the documentation. There are multiple ways to do this (not necessarly incompatible between them):
afaik, nbsphinx can be changed with myst-nb without needing to do any changes to the documentation, then rst files could be progressively updated to ipynb, myst or any other format supported by jupytext, rst, markdown and notebook sources can all be used at the same time to generate the documentation and link from one to the other with sphinx roles and cross references. Is this something that sounds interesting? I could update the infrastructure at some point whenever I have time and update a page (to any or multiple of the options above) as an example and then let other people take over |
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1198717318 | PR_kwDOAMm_X8418Vqw | 6464 | Add xarray-einstats to ecosystem page | OriolAbril 23738400 | closed | 0 | 1 | 2022-04-09T17:12:37Z | 2022-04-09T19:40:39Z | 2022-04-09T19:37:01Z | CONTRIBUTOR | 0 | pydata/xarray/pulls/6464 | Adds a mention of xarray-einstats to the ecosystem page. Related to #3322. |
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626215981 | MDExOlB1bGxSZXF1ZXN0NDI0MjQ5MzI4 | 4103 | keep attrs in reset_index | OriolAbril 23738400 | closed | 0 | 7 | 2020-05-28T05:00:50Z | 2020-06-05T19:42:54Z | 2020-06-05T19:39:10Z | CONTRIBUTOR | 0 | pydata/xarray/pulls/4103 | Modifies the code in Regarding multiindex, I think it is not possible to keep the metadata as it is removed when creating the multiindex/stacking.
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626063031 | MDU6SXNzdWU2MjYwNjMwMzE= | 4101 | reset_index does not keep attributes | OriolAbril 23738400 | closed | 0 | 1 | 2020-05-27T22:01:09Z | 2020-06-05T19:39:10Z | 2020-06-05T19:39:10Z | CONTRIBUTOR | If an indexing coordinate with attributes is converted to a non indexing coordinate with MCVE Code Sample```python temp = 15 + 8 * np.random.randn(2, 2, 3) time = xr.DataArray(pd.date_range('2014-09-06', periods=3), dims=["time"]).assign_attrs({"attr": 23}) coord = xr.DataArray([[-99.83, -99.32], [-99.79, -99.23]], dims=["x", "y"]).assign_attrs({"coord": True}) ds = xr.Dataset( { 'temperature': (['x', 'y', 'time'], temp), }, coords={ 'coord_0': coord, 'time': time, } ) ds both coord_0 and time have attributesds.reset_index("time") coordinate time_ does not have attributes anymoreds.reset_coords("coord_0") data variable coord_0 still has attributes``` Expected OutputI would expect attributes to be kept. Possible solutionI was wondering if changing this line and this other line to
could solve this. If so I'll send a PR whenever I can. VersionsOutput of <tt>xr.show_versions()</tt>INSTALLED VERSIONS ------------------ commit: None python: 3.6.9 (default, Apr 18 2020, 01:56:04) [GCC 8.4.0] python-bits: 64 OS: Linux OS-release: 4.15.0-101-generic machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: en_US.UTF-8 LOCALE: en_US.UTF-8 libhdf5: 1.10.4 libnetcdf: 4.6.3 xarray: 0.15.1 pandas: 1.0.3 numpy: 1.18.4 scipy: 1.4.1 netCDF4: 1.5.3 pydap: None h5netcdf: None h5py: 2.10.0 Nio: None zarr: None cftime: 1.0.4.2 nc_time_axis: None PseudoNetCDF: None rasterio: None cfgrib: None iris: None bottleneck: None dask: None distributed: None matplotlib: 3.2.1 cartopy: None seaborn: 0.10.1 numbagg: None setuptools: 42.0.2 pip: 20.1.1 conda: None pytest: 4.6.2 IPython: 7.14.0 sphinx: 2.0.0 |
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462122623 | MDU6SXNzdWU0NjIxMjI2MjM= | 3056 | Argument and its type joined in docs | OriolAbril 23738400 | closed | 0 | 2 | 2019-06-28T16:48:27Z | 2019-08-02T21:17:43Z | 2019-08-02T21:17:43Z | CONTRIBUTOR | This issue has nearly no effect on users, but (at least for me) it is quite bothering aesthetically. It also looks like something simple to solve even though I am not an sphinx expert so I am not sure. In the docstring, there is a colon between the name of one argument and its type, however, in the online documentation, the name and the type are smashed together. In the case of
I think it would be more readable and appealing if there was some kind of separation between the two. |
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457716471 | MDU6SXNzdWU0NTc3MTY0NzE= | 3032 | apply_ufunc should preemptively broadcast | OriolAbril 23738400 | open | 0 | 11 | 2019-06-18T22:02:36Z | 2019-06-19T22:27:27Z | CONTRIBUTOR | Code SampleI am having some troubles understanding ```python import xarray as xr import numpy as np a = xr.DataArray(data=np.random.normal(size=(7, 3)), dims=["dim1", "dim2"]) c = xr.DataArray(data=np.random.normal(size=(5, 6)), dims=["dim3", "dim4"]) def func(x,y): print(x.shape) print(y.shape) return ``` The function defined always raises an error when trying to call Problem description```python xr.apply_ufunc(func, a, c) Out(7, 3, 1, 1)(5, 6)``` Here, ```python print([ary.shape for ary in xr.broadcast(a,c)]) [(7, 3, 5, 6), (7, 3, 5, 6)]``` Using different input core dims does not get rid of the problem, instead I believe it shows some more issues: ```python xr.apply_ufunc(func, a, c, input_core_dims=[["dim1"],[]]) (3, 1, 1, 7), expected (3, 5, 6, 7)(5, 6), expected (3, 5, 6)xr.apply_ufunc(func, a, c, input_core_dims=[[],["dim3"]]) (7, 3, 1), expected (7, 3, 6)(6, 5), expected (7, 3, 6, 5)xr.apply_ufunc(func, a, c, input_core_dims=[["dim1"],["dim3"]]) (3, 1, 7), expected (3, 6, 7)(6, 5), expected (3, 6, 5)``` Is this current behaviour what should be expected? Output of
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xarray 13221727 | issue |
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